It's #ROCm getting better? Yes
Will you still use #CUDA? Yes.
https://www.youtube.com/watch?v=wCBLMXgk3No&t=933
What #AMD should focus on is to bring all of their SKU to use ROCm stable on all platforms. Currently that isn't possible, which is frustrating given their cards have more memory than #RTX at the same price.
#NVIDIA Bringing #CUDA To #RISCV
NVIDIA's drivers and CUDA software stack are predominantly supported on x86_64 and AArch64 systems but in the past was supported on IBM POWER. This week at the RISC-V Summit China event, NVIDIA's Frans Sijstermans announced that CUDA will be coming to RISC-V.
#AMD for their part with the upstream #opensource #AMDKFD kernel compute driver can already build on RISC-V and the #ROCm user-space components can also be built on RISC-V.
https://www.phoronix.com/news/NVIDIA-CUDA-Coming-To-RISC-V
New #ZLUDA 5 Preview Released For #CUDA On Non-NVIDIA #GPU
For now this ability to run unmodified CUDA apps on non-#NVIDIA GPUs is focused on #AMD GPUs of the #Radeon RX 5000 series and newer, which is AMD Radeon GPUs with #ROCm. Besides CUDA code samples, GeekBench has been one of the early targets for testing.
https://www.phoronix.com/news/ZLUDA-5-preview.43
It's convenient that I can use #LLMs to help me learn how to use LLMs because I'm pretty sure I wouldn't be able to figure it out any other way.
I want to use my local #Ollama models with #Copilot in #VSCode, but I have an #AMD #GPU so apparently I need to install something called the #ROCm (Radeon Open Compute Platform) via the Windows 11 HIP SDK?
And maybe all this doesn't work in #WSL, so I'll have to reinstall it in #Ubuntu there if I want to use it in one of those workspaces?
#ZLUDA Making Progress In 2025 On Bringing #CUDA To Non-NVIDIA #GPU
ZLUDA #opensource effort that started half-decade ago as drop-in CUDA implementation for #Intel GPUs and then for several years was funded by ##AMD as a CUDA implementation for #Radeon GPUs atop #ROCm and then open-sourced but then reverted has been continuing to push along a new path since last year. Current take on ZLUDA is a multi-vendor CUDA implementation for non-NVIDIA GPUs for #AI workloads & more.
https://www.phoronix.com/news/ZLUDA-Q2-2025-Update
I want to get #davinci_resolve working on #Fedora 42 with my now very old AMD rx480 8GB but it uses #OpenCL. The obvious choice would be #rocm but that dropped support for my GPU years ago and from what I found also causes issues with Davinci resolve for even more years. The other obvious choice would be mesas implementation but while #Rusticl improved things it's still not a feature complete implementation and rather slow. Is it smart to use the amdgpu-pro ICD with mesa drivers for this?
Omniwise: Predicting GPU Kernels Performance with LLMs
@eugenialoli same with photo #raw processing, non of the #foss apps use the color profiles of the cameras, no 16bit raw and many other issues. I gave up retouch due to the still bad gimp ux and the bad implementation of non destructive editing.
The sad reality is the #linuxdesktop is not ready for professional #mediaproduction and this is such a bad thing in times like this.
#davinciresolve also barely runs on everything except nvidia on #linux and still has no #flatpak
Even blender is a pain with amd #rocm
Any #Linux #kernel ,
#graphics or #GPU people out there?
I'm trying to understand the relationship between the #amgdpu driver shipped with the kernel; and the "andgpu-dkms" driver that comes with #ROCm .
Specifically, with a recent enough kernel, do we really need to install the ROCm version of the driver? Does the ROCm version contain stuff the general driver does not? Or is the ROCm stack (esp. libhsa) tightly tied to a very specific version of the driver?
#AMD splits #ROCm toolkit into two parts – ROCm #AMDGPU drivers get their own branch under Instinct #datacenter #GPU moniker
The new #datacenter Instinct driver is a renamed version of the #Linux AMDGPU driver packages that are already distributed and documented with ROCm. Previously, everything related to ROCm (including the amdgpu driver) existed as part of the ROCm software stack.
https://www.tomshardware.com/pc-components/gpus/amd-splits-rocm-toolkit-into-two-parts-rocm-amdgpu-drivers-get-their-own-branch-under-instinct-datacenter-gpu-moniker
ffs, why does their docker only support Navi 31 and not Navi 32? 
https://hub.docker.com/r/rocm/pytorch
I just wish both #Nvidia and #AMD would stop with that whole licensing bullshit around #CUDA and #ROCm and just include that damn stuff in the default driver.
I just want to run #Codestral on my local machine so I can use it with non-public code. Will be troublesome enough to cram it into 16gb VRAM. 
#computer #Linux #AI
AMD Working To Release MES Documentation & Source Code
"[..], AMD now says they will be releasing documentation followed by the source code for their Micro-Engine Scheduler (MES) IP block found within Radeon GPUs."
Note: towards the end of May
People running 7900 XTX cards under Linux: what’s the state of ROCm like for you?
Installs at all?
Installs and runs examples?
Toy programs?
Real programs?
